Systems and methods for matching, selecting, narrowcasting, and/or classifying based on rights management and/or other information

Abstract

Rights management information is used at least in part in a matching, narrowcasting, classifying and/or selecting process. A matching and classification utility system comprising a kind of Commerce Utility System is used to perform the matching, narrowcasting, classifying and/or selecting. The matching and classification utility system may match, narrowcast, classify and/or select people and/or things, non-limiting examples of which include software objects. The Matching and Classification Utility system may use any pre-existing classification schemes, including at least some rights management information and/or other qualitative and/or parameter data indicating and/or defining classes, classification systems, class hierarchies, category schemes, class assignments, category assignments, and/or class membership. The Matching and Classification Utility may also use at least some rights management information together with any artificial intelligence, expert system, statistical, computational, manual, or any other means to define new classes, class hierarchies, classification systems, category schemes, and/or assign persons, things, and/or groups of persons and/or things to at least one class.

Claims

We claim:

1. A method for narrowcasting selected digital information involving a plurality of first appliances and a second appliance, the plurality of first appliances each being located remotely from the second appliance, the second appliance and at least one of the first appliances including a secure node used to process rights management information, including:

(a) at the second appliance, securely receiving from plural of the first appliances user rights management information associated with plural users and processing the received user rights management information in the second appliance's secure node;

(b) using the received user rights management information in a process of creating a user class hierarchy;

(c) assigning a user to a user class defined by the user class hierarchy, the assignment based at least in part on the received user rights management information;

(d) associating digital rights management information with digital information;

(e) defining a digital information class hierarchy at least in part based on the digital rights management information;

(f) assigning the digital information to a digital information class defined by the digital information class hierarchy, the assignment based at least in part on the digital rights management information;

(g) matching the digital information class with the user class, the matching based at least in part on rights management information;

(h) selecting the digital information;

(i) selecting the user; and

(j) sending the digital information and associated rights management information to the user.

2. The method of claim 1 in which the user rights management information is received in at least one secure container and the step of sending the digital information and associated rights management information to the user further includes storing the digital information and associated rights management information in at least one secure container and sending the at least one secure container to the user.

3. The method of claim 1 wherein the digital information and associated rights management information are sent to the user in the same secure container.

4. The method of claim 1 including the further step of at least one user appliance having a secure node receiving the digital information and associated rights management information, and the further step of using said digital information, the use governed by the secure node in accordance with the received associated rights management information.

5. The method of claim 1 including the further step of the secure node processing the secure container and using the received digital information, the use governed by the secure node in accordance with the received associated rights management information.

6. The method of claim 1 wherein said received user rights management information includes payment rules and controls information.

7. The method of claim 1 wherein said received user rights management information includes usage audit information.

8. The method of claim 1 wherein said received user rights management information includes membership card information.

9. The method of claim 1 wherein said received user rights management information includes digital certificate information.

10. The method of claim 1 wherein said sending to the user step the digital information is at least in part transaction information.

11. The method of claim 1 wherein said sending to the user step the digital information is at least in part event information.

12. The method of claim 1 wherein said sending to the user step the digital information is at least in part hard goods purchase information.

13. The method of claim 1 wherein said sending to the user step the digital information is at least in part entertainment information.

14. The method of claim 13 wherein said entertainment information is at least in part music information.

15. The method of claim 1 wherein said sending to the user step the digital information is at least in part executable software.

16. The method of claim 1 wherein said associated rights management information includes audit record information.

17. The method of claim 1 wherein said associated rights management information at least in part governs saving the digital information outside the secure environment.

18. The method of claim 1 wherein said associated rights management information at least in part governs modification of the digital information.

19. The method of claim 1 wherein said associated rights management information at least in part governs creation of an excerpt of the digital information.

20. The method of claim 1 wherein said associated rights management information at least in part governs reformatting the digital information.

21. The method of claim 1 wherein said associated rights management information at least in part governs using the digital information in the creation of at least one derivative work that incorporates at least a part of the digital information.

22. The method of claim 1 wherein said sending to the user step the associated rights management information includes at least some rules and controls governing use of the digital information in at least one specified sovereignty.

23. The method of claim 1 wherein said sending to the user step the associated rights management information at least in part governs at least one value chain right.

24. The method of claim 1 wherein said sending to the user step the associated rights management information at least in part governs at least one right in a chain of handling and control.

25. The method of claim 1 wherein said sending to the user step the associated rights management information at least in part uses digital certificate information.

26. The method of claim 1 wherein said sending to the user step the associated rights management information at least in part uses membership card information.

27. The method of claim 1 wherein said sending to the user step the associated rights management information at least in part uses user attribute information.

28. The method of claim 1 wherein said sending to the user step the associated rights management information at least in part governs usage audit record creation.

29. The method of claim 1 wherein said sending to the user step the associated rights management information at least in part governs payment record creation.

30. The method of claim 1 wherein said sending to the user step the associated rights management information specifies at least one clearinghouse acceptable to rightsholders.

31. The method of claim 30 wherein said at least one acceptable clearinghouse is a financial clearinghouse.

32. The method of claim 30 wherein said at least one acceptable clearinghouse is a usage clearinghouse.

33. The method of claim 30 wherein said at least one acceptable clearinghouse is a rights and permissions clearinghouse.

34. The method of claim 30 wherein said at least one acceptable clearinghouse is a secure directory service.

35. The method of claim 30 wherein said at least one acceptable clearinghouse is a transaction authority clearinghouse.

36. The method of claim 30 wherein said at least one acceptable clearinghouse is a certificate authority clearinghouse.

37. The method of claim 1 wherein the user or digital information class hierarchy is determined at least in part using at least one statistical technique identifying at least one cluster of instances sharing similar profiles or features.

38. The method of claim 1 wherein the user or digital information class hierarchy is determined at least in part using numerical taxonomy techniques.

39. The method of claim 1 wherein the user or digital information class hierarchy is determined at least in part using at least one of cluster analysis, factor analysis, components analysis, and other similar data reduction or classification techniques.

40. The method of claim 1 wherein the user or digital information class hierarchy is determined at least in part using at least one pattern classification technique, including components analysis and neural approaches.

41. The method of claim 1 wherein the user or digital information class hierarchy is determined at least in part using at least one statistical technique that identifies at least one underlying dimension of qualities, traits, features, and characteristics, and assigning parameter data indicating the extent to which a given instance has, possesses, or may be characterized by the underlying dimension, factor, class, or result in the definition of at least one class or the assignment of at least one instance to at least one class.

42. The method of claim 1 wherein the user or digital information class hierarchy is determined at least in part using at least one statistical method employing fuzzy logic and fuzzy measurement or whose assignment to at least one class entails probabilities different from 1 or zero.

43. The method of claim 1 wherein the user or digital information class hierarchy is determined at least in part using at least one Baysian statistical classification techniques that uses an estimate of prior probabilities in determining class definitions or the assignment of at least one instance to at least one class.

44. The method of claim 1 wherein the user or digital information class hierarchy is determined at least in part using at least one statistical or graphical classification or data reduction method that uses rotation of reference axes, regardless of whether orthogonal or oblique rotations are used.

45. The method of claim 1 wherein the user or digital information class hierarchy is determined at least in part using at least one statistical method for two and three way multidimensional scaling.

46. The method of claim 1 wherein at least one first appliance is a personal computer.

47. The method of claim 1 wherein at least one first appliance is a consumer electronics appliance.

48. A method for narrowcasting selected digital information to specified recipients, including:

(a) at a receiving appliance, receiving selected digital information from a sending appliance remote from the receiving appliance, the receiving appliance having a secure node and being associated with a specified recipient;

(i) the digital information having been selected at least in part based on the digital information's membership in a first class, wherein the first class membership was determined at least in part using rights management information; and

(ii) the specified recipient having been selected at least in part based on membership in a second class, wherein the second class membership was determined at least in part on the basis of information derived from the specified recipient's creation, use of, or interaction with rights management information; and

(b) the specified recipient using the receiving appliance to access the received selected digital information in accordance with rules and controls, associated with the selected digital information, the rules and controls being enforced by the receiving appliance secure node.

49. The method of claim 48 wherein the first or second class membership is determined at least in part using rights management information that includes payment rules and controls information.

50. The method of claim 48 wherein the first or second class membership is determined at least in part using rights management information that includes audit record information.

51. The method of claim 48 wherein the first or second class membership is determined at least in part using rights management information that governs saving the associated digital information outside a protected environment.

52. The method of claim 48 wherein the first or second class membership is determined at least in part using rights management information that governs modifying the associated digital information.

53. The method of claim 48 wherein the first or second class membership is determined at least in part using rights management information that governs creating an excerpt of the associated digital information.

54. The method of claim 48 wherein the first or second class membership is determined at least in part using rights management information that governs using the associated digital information in the creation of at least one derivative work that incorporates at least part of the digital information.

55. The method of claim 48 wherein the first or second class membership is determined at least in part using rights management information that includes usage audit information.

56. The method of claim 48 wherein the first or second class membership is determined at least in part using rights management information that includes membership card information.

57. The method of claim 48 wherein the first or second class membership is determined at least in part using rights management information that includes digital certificate information.

58. The method of claim 48 wherein said received selected digital information is at least in part transaction information.

59. The method of claim 48 wherein said received selected digital information is at least in part event information.

60. The method of claim 48 wherein said received selected digital information is at least in part hard goods purchase information.

61. The method of claim 48 wherein said received selected digital information is at least in part entertainment information.

62. The method of claim 61 wherein said entertainment information is at least in part music information.

63. The method of claim 48 wherein said received selected digital information is at least in part executable software.

64. The method of claim 48 wherein said rules and controls at least in part govern use in at least one specified sovereignty.

65. The method of claim 48 wherein said rules and controls include at least one value chain rule and control.

66. The method of claim 48 wherein said rules and controls include governing at least one right in a chain of handling and control.

67. The method of claim 48 wherein said rules and controls at least in part use digital certificate information.

68. The method of claim 48 wherein said rules and controls at least in part use membership card information.

69. The method of claim 48 wherein said rules and controls at least in part use user attribute information.

70. The method of claim 48 wherein said rules and controls at least in part govern usage audit record creation.

71. The method of claim 48 wherein said rules and controls that at least in part govern payment record creation.

72. The method of claim 48 wherein said rules and controls in part specifying at least one clearinghouse acceptable to rightsholders.

73. The method of claim 72 wherein said at least one acceptable clearinghouse is a financial clearinghouse.

74. The method of claim 72 wherein said at least one acceptable clearinghouse is a usage clearinghouse.

75. The method of claim 72 wherein said at least one acceptable clearinghouse is a rights and permissions clearinghouse.

76. The method of claim 72 wherein said at least one acceptable clearinghouse is a secure directory service.

77. The method of claim 72 wherein said at least one acceptable clearinghouse is a transaction authority clearinghouse.

78. The method of claim 72 wherein said at least one acceptable clearinghouse is a VDE administration clearinghouse.

79. The method of claim 72 wherein said at least one acceptable clearinghouse is a certificate authority clearinghouse.

80. The method of claim 48 wherein the first or second class membership is determined at least in part using at least one statistical technique identifying at least one cluster of instances sharing similar profiles or features.

81. The method of claim 48 wherein the first or second class membership is determined at least in part using numerical taxonomy techniques.

82. The method of claim 48 wherein the first or second class membership is determined at least in part using at least one of cluster analysis, factor analysis, components analysis, and other similar data reduction or classification techniques.

83. The method of claim 48 wherein the first or second class membership is determined at least in part using at least one pattern classification technique, including components analysis and neural approaches.

84. The method of claim 48 wherein the first or second class membership is determined at least in part using at least one statistical technique that identifies at least one underlying dimension of qualities, traits, features, or characteristics, and assigning parameter data indicating the extent to which a given instance has, possesses, or may be characterized by the underlying dimension, factor, class, or result in the definition of at least one class or the assignment of at least one instance to at least one class.

85. The method of claim 48 wherein the first or second class membership is determined at least in part using at least one statistical method employing fuzzy logic or fuzzy measurement or whose assignment to at least one class entails probabilities different from 100 or zero.

86. The method of claim 48 wherein the first or second class membership is determined at least in part using at least one Baysian statistical classification techniques that uses an estimate of prior probabilities in determining class definitions or the assignment of at least one instance to at least one class.

87. The method of claim 48 wherein is determined at least in part using at least one statistical or graphical classification or data reduction method that uses rotation of reference axes, regardless of whether orthogonal or oblique rotations are used.

88. The method of claim 48 wherein the first or second class membership is determined at least in part using at least one statistical method for two and three way multidimensional scaling.

89. The method of claim 48 wherein said receiving appliance is a personal computer.

90. The method of claim 48 wherein said receiving appliance is a consumer electronics appliance.

91. A method for securely narrowcasting selected digital information to specified recipients including:

(a) receiving selected digital information in a secure container at a receiving appliance remote from a sending appliance, the receiving appliance having a secure node, the receiving appliance being associated with a receiving entity;

(i) the digital information having been selected at least in part based on the digital information's membership in a first class,

(ii) the first class membership having been determined at least in part using rights management information;

(b) the receiving entity having been selected at least in part based on said receiving entity's membership in a second class,

(i) the second class membership having been determined at least in part on the basis of information derived from the recipient entity's creation, use of, or interaction with rights management information;

(c) receiving at the receiving appliance rules and controls in a secure container,

(i) the rules and controls having been associated with the selected digital information; and

(d) using at the receiving appliance the selected digital information in accordance with the rules and controls,

(i) the rules and controls being enforced by the receiving appliance secure node.

92. The method of claim 91 wherein the first or second class membership is determined at least in part using rights management information that includes payment rules and controls information.

93. The method of claim 91 wherein the first or second class membership is determined at least in part using rights management information that includes audit record information.

94. The method of claim 91 wherein the first or second class membership is determined at least in part using that includes controls for saving associated digital information outside the secure environment.

95. The method of claim 91 wherein the first or second class membership is determined at least in part using rights management information that includes controls for modifying the associated digital information.

96. The method of claim 91 wherein the first or second class membership is determined at least in part using rights management information that includes controls for creating an excerpt of the associated digital information.

97. The method of claim 91 wherein the first or second class membership is determined at least in part using rights management information that includes controls for using the associated digital information in the creation of at least one derivative work that incorporates at least part of the associated digital information.

98. The method of claim 91 wherein the first or second class membership is determined at least in part using rights management information that includes usage audit information.

99. The method of claim 91 wherein the first or second class membership is determined at least in part using rights management information that includes membership card information.

100. The method of claim 91 wherein the first or second class membership is determined at least in part using rights management information that includes digital certificate information.

101. The method of claim 91 wherein said received selected digital information includes transaction information.

102. The method of claim 91 wherein said received selected digital information includes event information.

103. The method of claim 91 wherein said received selected digital information includes hard goods purchase information.

104. The method of claim 91 wherein said received selected digital information includes entertainment information.

105. The method of claim 91 wherein said received selected digital information includes executable software.

106. The method of claim 91 wherein said rules and controls at least in part govern use in at least one specified sovereignty.

107. The method of claim 91 wherein said rules and controls govern at least one value chain right.

108. The method of claim 91 wherein said rules and controls at least in part govern at least one right in a chain of handling and control.

109. The method of claim 91 wherein said rules and controls at least in part use digital certificate information.

110. The method of claim 91 wherein said rules and controls at least in part use membership card information.

111. The method of claim 91 wherein said rules and controls at least in part use user attribute information.

112. The method of claim 91 wherein said rules and controls at least in part govern usage audit record creation.

113. The method of claim 91 wherein said rules and controls at least in part govern payment record creation.

114. The method of claim 91 wherein said rules and controls specify at least one clearinghouse acceptable to rightsholders.

115. The method of claim 114 wherein said at least one acceptable clearinghouse is a financial clearinghouse.

116. The method of claim 114 wherein said at least one acceptable clearinghouse is a usage clearinghouse.

117. The method of claim 114 wherein said at least one acceptable clearinghouse is a rights and permissions clearinghouse.

118. The method of claim 114 wherein said at least one acceptable clearinghouse is a secure directory service.

119. The method of claim 114 wherein said at least one acceptable clearinghouse is a transaction authority clearinghouse.

120. The method of claim 114 wherein said at least one acceptable clearinghouse is a VDE administration clearinghouse.

121. The method of claim 114 wherein said at least one acceptable clearinghouse is a certificate authority clearinghouse.

122. The method of claim 91 wherein the first or second class membership is determined at least in part using at least one statistical technique identifying at least one cluster of instances sharing similar profiles or features.

123. The method of claim 91 wherein the first or second class membership is determined at least in part using numerical taxonomy techniques.

124. The method of claim 91 wherein the first or second class membership is determined at least in part using at least one of cluster analysis, factor analysis, components analysis, and other similar data reduction or classification techniques.

125. The method of claim 91 wherein the first or second class membership is determined at least in part using at least one pattern classification technique, including components analysis and neural approaches.

126. The method of claim 91 wherein the first or second class membership is determined at least in part using at least one statistical technique that identifies at least one underlying dimension of qualities, traits, features, or characteristics, and assigning parameter data indicating the extent to which a given instance has, possesses, or may be characterized by the underlying dimension, factor, class, or result in the definition of at least one class or the assignment of at least one instance to at least one class.

127. The method of claim 91 wherein the first or second class membership is determined at least in part using at least one statistical method employing fuzzy logic or fuzzy measurement or whose assignment to at least one class entails probabilities different from 200 or zero.

128. The method of claim 91 wherein the first or second class membership is determined at least in part using at least one Baysian statistical classification techniques that uses an estimate of prior probabilities in determining class definitions or the assignment of at least one instance to at least one class.

129. The method of claim 91 wherein the first or second class membership is determined at least in part using at least one statistical or graphical classification or data reduction method that uses rotation of reference axes, regardless of whether orthogonal or oblique rotations are used.

130. The method of claim 91 wherein the first or second class membership is determined at least in part using at least one statistical method for two and three way multidimensional scaling.

131. The method of claim 91 wherein said receiving appliance is a personal computer.

132. The method of claim 91 wherein said receiving appliance is a consumer electronics appliance.

133. A method for operating a subject switching system including:

(a) at the subject switch, receiving information identifying a class hierarchy made up of one or more digital information classes from a remote source,

(i) the class hierarchy having been defined at least in part using rights management information associated with digital information,

(ii) the class hierarchy having been used to classify the digital information, classification based at least in part on the rights management information;

(b) the subject switch publishing the class hierarchy to a user located remotely from the subject switch, the user having a user appliance containing a secure node;

(c) the user subscribing to one of the digital information classes;

(d) the user appliance monitoring received messages for digital information in the subscribed digital information class;

(e) the user appliance identifying one such received message;

(f) receiving at the user appliance rights management information associated with the identified digital information; and

(g) using at the user appliance the identified digital information in accordance with the received rights management information, the use governed by the user appliance secure node.

134. The method of claim 133 wherein said using step the identified digital information is at least in part transaction information.

135. The method of claim 133 wherein said using step the identified digital information is at least in part event information.

136. The method of claim 133 wherein said using step the identified digital information is at least in part hard goods purchase information.

137. The method of claim 133 wherein said using step the identified digital information is at least in part entertainment information.

138. The method of claim 133 wherein said using step the identified digital information is at least in part executable software.

139. The method of claim 133 wherein said class hierarchy defining step said rights management information includes audit record information.

140. The method of claim 133 wherein said class hierarchy defining step, said rights management information includes at least some rules and controls information.

141. The method of claim 133 wherein said rules and controls at least in part govern saving associated digital information out of the protected environment.

142. The method of claim 133 wherein said rules and controls at least in part govern modification of the associated digital information.

143. The method of claim 133 wherein said rules and controls at least in part govern creation of an excerpt of the associated digital information.

144. The method of claim 133 wherein said rules and controls at least in part govern reformatting the associated digital information.

145. The method of claim 133 wherein said rules and controls at least in part govern creation of at least one derivative work that incorporates at least a part of the associated digital information.

146. The method of claim 133 wherein said receiving at the subject switch step includes receiving class hierarchy information in a secure container.

147. The method of claim 133 wherein said monitoring step includes monitoring messages that are received at least in part in a secure container.

148. The method of claim 133 wherein said receiving at the user appliance step include receiving rules and controls in a secure container.

149. The method of claim 133 wherein said receiving at the user appliance step includes receiving identified digital information and associated rules and controls in the same secure container.

150. The method of claim 133 wherein said receiving at the user appliance step said rights management information includes rules and controls governing use in at least one specified sovereignty.

151. The method of claim 133 wherein said receiving at the user appliance step said rights management information includes rules and controls governing at least one value chain right.

152. The method of claim 133 wherein said receiving at the user appliance step said rights management information includes rules and controls governing at least one right in a chain of handling and control.

153. The method of claim 133 wherein said receiving at the user appliance step said rights management information includes rules and controls that use digital certificate information.

154. The method of claim 133 wherein said receiving at the user appliance step said rights management information includes rules and controls that use membership card information.

155. The method of claim 133 wherein said receiving at the user appliance step said rights management information includes rules and controls that use user attribute information.

156. The method of claim 133 wherein said receiving at the user appliance step said rights management information includes rules and controls that govern usage audit record creation.

157. The method of claim 133 wherein said receiving at the user appliance step said rights management information includes rules and controls specifying at least one clearinghouse acceptable to rightsholders.

158. The method of claim 157 wherein said at least one acceptable clearinghouse is a financial clearinghouse.

159. The method of claim 157 wherein said at least one acceptable clearinghouse is a usage clearinghouse.

160. The method of claim 157 wherein said at least one acceptable clearinghouse is a rights and permissions clearinghouse.

161. The method of claim 157 wherein said at least one acceptable clearinghouse is a secure directory service.

162. The method of claim 157 wherein said at least one acceptable clearinghouse is a transaction authority clearinghouse.

163. The method of claim 157 wherein said at least one acceptable clearinghouse is a VDE administration clearinghouse.

164. The method of claim 157 wherein said at least one acceptable clearinghouse is a certificate authority clearinghouse.

165. The method of claim 133 wherein said class hierarchy is determined at least in part using at least one statistical technique identifying at least one cluster of instances sharing similar profiles or features.

166. The method of claim 133 wherein said class hierarchy is determined at least in part using numerical taxonomy techniques.

167. The method of claim 133 wherein said class hierarchy is determined at least in part using at least one of cluster analysis, factor analysis, components analysis, and other similar data reduction or classification techniques.

168. The method of claim 133 wherein said class hierarchy is determined at least in part using at least one of cluster analysis, factor analysis, components analysis, and other similar data reduction or classification techniques.

169. The method of claim 133 wherein said class hierarchy is determined at least in part using at least one pattern classification technique, including components analysis and neural approaches.

170. The method of claim 133 wherein said class hierarchy is determined at least in part using at least one statistical technique that identifies at least one underlying dimension of qualities, traits, features, or characteristics, and assigning parameter data indicating the extent to which a given instance has, possesses, or may be characterized by the underlying dimension, factor, class, or result in the definition of at least one class or the assignment of at least one instance to at least one class.

171. The method of claim 133 wherein said class hierarchy is determined at least in part using at least one statistical method employing fuzzy logic or fuzzy measurement or whose assignment to at least one class entails probabilities different from 1 or zero.

172. The method of claim 133 wherein said class hierarchy is determined at least in part using at least one Baysian statistical classification techniques that uses an estimate of prior probabilities in determining class definitions or the assignment of at least one instance to at least one class.

173. The method of claim 133 wherein said class hierarchy is determined at least in part using at least one statistical or graphical classification or data reduction method that uses rotation of reference axes, regardless of whether orthogonal or oblique rotations are used.

174. The method of claim 133 wherein said class hierarchy is determined at least in part using at least one statistical method for two and three way multidimensional scaling.

175. The method of claim 133 wherein said using step the user appliance is a personal computer.

176. The method of claim 133 wherein said using step the user appliance is a consumer electronics appliance.

177. A method for operating a subject switching system including:

(a) at the subject switch, receiving rights management information associated with digital information from at least one remote source;

(b) creating at the subject switch a class hierarchy made up of one or more digital information classes,

(i) the class hierarchy having been defined at least in part using rights management information associated with digital information,

(ii) the class hierarchy having been used to classify the digital information, classification based at least in part on the rights management information;

(c) the subject switch publishing the class hierarchy to a user located remotely from the subject switch, the user having a user appliance containing a secure node;

(d) the user subscribing to one of the digital information classes;

(e) the user appliance monitoring received messages for digital information in the subscribed digital information class;

(f) the user appliance identifying one such received message;

(g) receiving at the user appliance rights management information associated with the identified digital information; and

(h) using at the user appliance the identified digital information in accordance with the received rights management information, the use governed by the user appliance secure node.

178. The method of claim 177 wherein said using step the identified digital information is at least in part transaction information.

179. The method of claim 177 wherein said using step the identified digital information is at least in part event information.

180. The method of claim 177 wherein said using step the identified digital information is at least in part hard goods purchase information.

181. The method of claim 177 wherein said using step the identified digital information is at least in part entertainment information.

182. The method of claim 177 wherein said using step the identified digital information is at least in part executable software.

183. The method of claim 177 wherein said class hierarchy defining step said rights management information includes audit record information.

184. The method of claim 177 wherein said class hierarchy defining step, said rights management information includes at least some rules and controls.

185. The method of claim 184 wherein said rules and controls at least in part govern saving the associated digital information out of the protected environment.

186. The method of claim 184 wherein said rules and controls at least in part govern modification of the associated digital information.

187. The method of claim 184 wherein said rules and controls at least in part govern creation of an excerpt of the associated digital information.

188. The method of claim 184 wherein said rules and controls at least in part govern reformatting the associated digital information.

189. The method of claim 184 wherein said rules and controls at least in part govern creation of at least one derivative work that incorporates at least part of the associated digital information.

190. The method of claim 177 wherein said receiving at the subject switch step includes receiving class hierarchy information in a secure container.

191. The method of claim 177 wherein said monitoring step includes monitoring messages received at least in part in a secure container.

192. The method of claim 177 wherein said receiving at the user appliance step include receiving rules and controls in a secure container.

193. The method of claim 177 wherein said receiving at the user appliance step includes receiving identified digital information and associated rules and controls in the same secure container.

194. The method of claim 177 wherein said receiving at the user appliance step said rights management information includes rules and controls governing use in at least one specified sovereignty.

195. The method of claim 177 wherein said receiving at the user appliance step said rights management information includes rules and controls governing at least one value chain right.

196. The method of claim 177 wherein said receiving at the user appliance step said rights management information includes rules and controls governing at least one right in a chain of handling and control.

197. The method of claim 177 wherein said receiving at the user appliance step said rights management information includes rules and controls that use digital certificate information.

198. The method of claim 177 wherein said receiving at the user appliance step said rights management information includes rules and controls that use membership card information.

199. The method of claim 177 wherein said receiving at the user appliance step said rights management information includes rules and controls that use user attribute information.

200. The method of claim 177 wherein said receiving at the user appliance step said rights management information includes rules and controls that govern usage audit record creation.

201. The method of claim 177 wherein said receiving at the user appliance step said rights management information includes rules and controls specifying at least one clearinghouse acceptable to rightsholders.

202. The method of claim 201 wherein said at least one acceptable clearinghouse is a financial clearinghouse.

203. The method of claim 201 wherein said at least one acceptable clearinghouse is a usage clearinghouse.

204. The method of claim 201 wherein said at least one acceptable clearinghouse is a rights and permissions clearinghouse.

205. The method of claim 201 wherein said at least one acceptable clearinghouse is a secure directory service.

206. The method of claim 201 wherein said at least one acceptable clearinghouse is a transaction authority clearinghouse.

207. The method of claim 201 wherein said at least one acceptable clearinghouse is a VDE administration clearinghouse.

208. The method of claim 201 wherein said at least one acceptable clearinghouse is a certificate authority clearinghouse.

209. The method of claim 177 wherein said class hierarchy is determined at least in part using at least one statistical technique identifying at least one cluster of instances sharing similar profiles or features.

210. The method of claim 177 wherein said class hierarchy is determined at least in part using numerical taxonomy techniques.

211. The method of claim 177 wherein said class hierarchy is determined at least in part using at least one of cluster analysis, factor analysis, components analysis, and other similar data reduction or classification techniques.

212. The method of claim 177 wherein said class hierarchy is determined at least in part using at least one of cluster analysis, factor analysis, components analysis, and other similar data reduction or classification techniques.

213. The method of claim 177 wherein said class hierarchy is determined at least in part using at least one pattern classification technique, including components analysis and neural approaches.

214. The method of claim 177 wherein said class hierarchy is determined at least in part using at least one statistical technique that identifies at least one underlying dimension of qualities, traits, features, or characteristics, and assigning parameter data indicating the extent to which a given instance has, possesses, or may be characterized by the underlying dimension, factor, class, or result in the definition of at least one class or the assignment of at least one instance to at least one class.

215. The method of claim 177 wherein said class hierarchy is determined at least in part using at least one statistical method employing fuzzy logic or fuzzy measurement or whose assignment to at least one class entails probabilities different from 1 or zero.

216. The method of claim 177 wherein said class hierarchy is determined at least in part using at least one Baysian statistical classification techniques that uses an estimate of prior probabilities in determining class definitions or the assignment of at least one instance to at least one class.

217. The method of claim 177 wherein said class hierarchy is determined at least in part using at least one statistical or graphical classification or data reduction method that uses rotation of reference axes, regardless of whether orthogonal or oblique rotations are used.

218. The method of claim 177 wherein said class hierarchy is determined at least in part using at least one statistical method for two and three way multidimensional scaling.

219. The method of claim 177 wherein said using step the user appliance is a personal computer.

220. The method of claim 177 wherein said using step the user appliance is a consumer electronics appliance.

Description

FIELDS OF THE INVENTIONS

The inventions relate to electronic rights and transaction management. More particularly, the inventions relate to automated systems, methods and techniques for efficiently matching, selecting, narrowcasting, categorizing and/or classifying in a distributed electronic rights and/or other event and/or transaction management environment. For example, the inventions provide electronic computer based systems, methods and techniques for matching, classifying, narrowcasting, and/or selecting digital information describing people and/or other things. This matching, classifying, narrowcasting, and/or selecting can be based, at least in part, on elements of rights management information and/or one or more other categories of information--wherein such information is used for efficient, trusted event management assuring the execution of one or more controls related to, including, for example, consequences of processing such digital information describing people and/or other things. The present inventions also provide systems and methods for efficiently determining class hierarchies, classification schemes, categories, and/or category schemes and/or the assignment of objects, persons and/or things to said class hierarchies, classification schemes, categories, and/or category schemes using at least some rights management information.

BACKGROUND AND SUMMARY OF THE INVENTIONS

The modern world gives us a tremendous variety and range of options and choices. Cable and satellite television delivers hundreds of different television channels each carrying a different program. The radio dial is crowded with different radio stations offering all kinds of music, news, talk, and anything else one may care to listen to. The corner convenience store carries newspapers from around the country, and a well stocked newsstand allows you to choose between hundreds of magazines and publications about nearly every subject you can think of. Merchandise from all corners of the world is readily available at the shopping mall or by mail order. You can pay by check, in cash, or using any number of different kinds of credit cards and ATM cards.

This tremendous variety is good, but it also presents problems. Sometimes, it is hard or inefficient for us to find what we want and need because there are too many things to evaluate and choose from, and they are often located in too many places. We can waste a lot of time searching for the things we need or want at the right price, with the rights features, and at a particular time.

Sometimes, we never find things that satisfy what we feel we need or want. This happens when we don't know what to look for, how to look for it, or don't have the necessary assistance or tools to search successfully. For example, we may not know the best way of looking for something. Sometimes, we know what we are looking for but can't express or articulate it in ways that help us look. And sometimes, we don't even know what we are looking for. You may know you need something, know its missing, but never really know how to communicate to others what you are looking for. For example, someone who speaks only English may never find resources using Japanese or Spanish. In general, we often don't have the time or resources to look for all the things that would give us the most benefit or make us the most satisfied.

It's Hard To Find Mass Media Things You Want Or Need

FIG. 1A shows, as one example, how frustrating it can be to find anything to watch on the hundreds of television channels that may be available. The man in FIG. 1A spends a lot of time "channel surfing," trying to find something he is interested in watching. He may be moderately interested in golf, but may not like the particular golf tournament or golf players being broadcast at 7 o'clock on a particular channel. After flipping through other channels, he might think an action movie looks interesting only to find out after watching it for a while that he isn't really interested in it after all. A documentary on horses also seems interesting at first, but he finds it boring after watching it awhile because it doesn't give him the kind of information he is interested in. The whole process can be frustrating and he may feel he wasted a lot of time. FIG. 1B shows the man getting so frustrated at the wasted time and energy that he thinks that maybe watching television is just not worth it. What the man really needs is a powerful yet efficient way to find those things that most satisfy his desires--that is, match his needs and/or his interests.

Our Mail Overloads Us With Things We Don't Want or Need

The same thing can happen with information sent to us in the mail. It can be fun to receive some kinds of mail, such as personal letters, or magazines and catalogs on topics of personal interest. Certain other mail, such as bills, may not be fun but are usually important. Unfortunately, our mailboxes are typically overflowing with yet another kind of mail commonly referred to as "junk mail." The person in FIG. 2 finds his mailbox stuffed to the overflowing point with mail he never asked for and has absolutely no interest in. Most of this junk mail ends up unread and in the trash. However, it can take a long time to sort through all this mail to be sure you are only throwing out only the junk mail and not the good mail you are interested in or need. For example, it's sometimes hard to distinguish credit card bills from offers for new credit cards you don't need or want. Wouldn't it be useful if your mail could be automatically "cleaned" of the mail you had no interest in and you received only the mail you wanted or needed?

Sorting through things to identify things you might want, then selecting what you actually want, can be a frustrating and time consuming experience. For example, it wastes the time of the person who receives the junk mail, and it also wastes the time, money and effort of the people who spend their money to send mail to people hoping that they will buy their products.

As frustrating as finding and selecting may be to consumers, they often create even greater problems for businesses and people who want to locate or provide information, goods and services. It is often said, that in the world of business, "Information is Power" and "efficiency is the key to success." To find or sell the most relevant or useful information and to provide the ability to most efficiently allow business to operate at its best, we need easy-to-use tools that can help us navigate, locate, and select what matches our interests. In the modern world, it is often difficult to find out what different people like, and to supply people with the opportunity to select the best or most satisfying choices.

Past attempts outside the computer world to match up people with information, goods and/or services have had limited success. For example, attempts to "target" mass mailings may increase the chance that they will go to people who are interested in them, but the entire process is still very wasteful and inefficient. It is considered a good success rate to match the interests of only a few percent of the recipients of "junk" mail. Telemarketing campaigns that use the telephone to reach potential consumers can be very expensive, very annoying to consumers who are not interested in the products being marketed, and very costly and inefficient. A much more ideal situation for all concerned is enabling businesses to send information only to individual consumers likely to find the information interesting, desirable, convincing, and/or otherwise useful. That way, businesses save time and money and consumers aren't unproductively hassled by information, phone calls, junk mail, junk e-mail and the like. However, right now it is extremely difficult to accomplish this goal, and so businesses continue to annoy consumers while wasting their own time, money, and effort.

Because of the Vast Amount of Information Available, Even Systems that Provide a High Degree of Organization May Be Difficult to Use or Access

You can find yourself wasting a lot of time finding things--even in places where finding things is supposed to be easy. For example, a library is a place where you can find all sorts of useful information but can also waste a lot of time trying to find what you are looking for. Modern libraries can be huge, containing tens or even hundreds of thousands or millions of different books, magazines, newspapers, video tapes, audio tapes, disks, and other publications. Most libraries have an electronic or manual card catalog that classifies and indexes all of those books and other materials. This classification system is useful, but it often has significant limitations.

For example, normally a card catalog will classify materials based only on a few characteristics (for example, general subject, author and title). The boy in FIG. 3 is looking for information on American League baseball teams during World War II for a high school report. The card catalog led to the general subject of baseball and other sports, but, looking at the catalog, he can't identify any books that seem to provide the specific information he wants to see, so he must rely on books classified as "histories of sports" or "histories of baseball." He can spend lots of time looking through the books on the shelves, going back to the card catalog, and going back to the shelves before he finds a reference that's reasonably helpful. He may need to go ask an expert (the librarian) who is familiar with the books the library has on sports and may know where to look for the information. Even then, the boy may need to flip through many different books and magazines, and look in many different places within the library before he finds the information he is looking for.

Finding Products You Want or Need Can Be Very Difficult and Time Consuming

The same kind of frustrating experience can happen when you shop for a particular kind of item. While some people enjoy shopping, and have fun seeing what is in various stores, many people dislike spending time shopping, searching for the best or most affordable item. And sometimes even people who like to shop don't have the time to shop for a specific item.

For example, the man in FIG. 4 goes into a shopping mall looking for a tie to fit very tall people. He didn't wear a tie to work that day, but, at the last minute, an important meeting was scheduled for later that day and he needs to dress up. The shopping mall has a large variety of stores, each selling a range of merchandise. But the man may only have a short time to look. For example, he may be on his lunch break, and needs to get back to work soon. He can't spend a lot of time shopping. He may therefore need to rely on tools to help him identify where he wants to buy the tie. Perhaps he uses a mall directory that classifies the different stores in terms of what kinds of merchandise they sell (for example, clothing, books, housewares, etc.). Perhaps he asks at the malls help desk staffed by "experts" who know what is available in the shopping mall. But even these resources may not tell him where to buy Italian silk ties that are discounted and cost $20. So he does the best he can with the available resources.

These Problems Are Worse in the Digital World

The electronic or digital world offers a rapidly growing, vast array of electronically published products and services. For example, computer superstores have a dizzying array of different software products. Furthermore, music is now published primarily in digital form on optical disks, and video will soon be published that way too. And, of particular interest related to certain of the inventions described by this document, the Internet now has millions of home pages with an overwhelmingly variety and quantity of digital information, and, these millions of home pages, in turn, point or "link" to millions of other web pages as well.

Today, for example, you can use the Internet to:

read electronic newspapers, books and magazines and see them on your computer screen;

get music in electronic form and play it using your computer;

send and receive electronic mail all over the world;

download reports and other information compiled by governments, companies, industries, universities, and individuals;

watch videos and animations;

play games with "cyber-friends" located around the world;

chat with individuals and groups who share at least some interests in common;

participate in "virtual reality" worlds, games, and/or experiences;

(offer to) buy, and/or (offer to) sell nearly anything; and

conduct electronic transactions and commerce.

Today on the Internet and you can also find nearly anything and everything you can possibly imagine, although finding exactly what you really want may be time consuming and frustrating. This is because the Internet and World Wide Web provide perhaps the best example of an environment that is particularly hard to navigate. There are an overwhelming number of choices--too many to easily relate to or understand--and many of which are terribly hard to find, even using the various Web searching "engines." The Internet is particularly exciting because it has the potential to provide to nearly everyone access to nearly every kind of information. Information can also come from an almost limitless variety of sources. But today, so much information on the Internet is superficial or useless, and too many choices can be more a curse than a blessing if you don't have meaningful, easy ways to eliminate all but a relatively few choices. And the situation will only become much worse as more Web sites appear, and as digital information is distributed in "objects" or "containers" providing enhanced security and privacy but possibly more difficult access and identifiability.

As time passes, more and more valuable and desirable information will be available in digital containers. However, unless tools are developed to solve the problem, there will be no efficient or satisfying means to sort through the potentially trillions of digital containers available on tens of millions of Web pages, to find containers satisfying a search or fulfilling an information need. Furthermore, existing information searching mechanisms typically provide no way to readily perform a search that matches against underlying commercial requirements of providers and users.

It Will Be Difficult to Find Rights Management Scenarios Matching Your Requirements

If, for example, you have an auto repair newsletter and you want to create an article containing information on auto repair of Ford Bronco vehicles, you may wish to look for detailed, three dimensional, step-by-step "blow-up" mechanical images of Ford Bronco internal components. Perhaps these are available from hundreds of sources (including from private individuals using new, sophisticated rendering graphics programs, as well as from engineering graphics firms). Given the nature of your newsletter, you have decided that your use of such images should cost you no more than one penny to redistribute per copy in quantities of several thousand--this low cost being particularly important since you will have numerous other costs per issue for acquiring rights to other useful digital information products which you reuse and, for example, enhance in preparing a particular issue. You therefore wish to search and match against rights management rules associated with such products--non-limiting examples of which include:

cost ceilings,

redistribution rights (e.g., limits on the quantity that may be redistributed),

modification rights,

class related usage rights,

category related usage rights,

sovereignty based licensing and taxation fees,

import and export regulations, and

reporting and/or privacy rights (you don't want to report back to the product provider the actual identity of your end users and/or customers.

If you can't match against your commercial requirements, you may be forced to waste enormous amounts of time sifting through all of the available products matching Ford Bronco internal components--or you may settle for a product that is far less than the best available (settling on the first adequate product that you review).

Computers Don't Necessarily Make It Easier to Find Things

Anyone who has ever used the Internet or the World Wide Web knows that networks, computers and electronics, when used together, do not necessarily make the overall task of finding information easier. In fact, computers can make the process seem much worse. Most Internet users will probably agree that trying to find things you are interested on the Internet can be a huge time drain. And the results can be very unsatisfactory. The rapid growth rate of information available on the Web is continually making this process of finding desired information even harder. You can spend many hours looking for information on a subject that interests you. In most cases, you will eventually find some information of value--but even using today's advanced computer search tools and on-line directories, it can take hours or days. With the advent of the technology advances developed by InterTrust Technologies Corp. and others, publishers will find it far more appealing to make their valuable digital information assets available on-line and to allow extractions and modifications of copyrighted materials that will vastly expand the total number of information objects. This will enormously worsen the problem, as the availability of valuable information products greatly expands.

It Is Usually Hard to Find Things On the Internet

There are many reasons why it is difficult to find what you want on the Internet. One key reason is that, unlike a public library, for example, there is no universal system to classify or organize electronic information to provide information for matching with what's important to the person who is searching. Unlike a library, it is difficult on the Internet to efficiently browse over many items since the number of possible choices may be much larger than the number of books on a library shelves and since electronic classification systems typically do not provide much in the way of physical cues. For example, when browsing library shelves, the size of a book, the number of pictures in the book, or pictures on magazine covers may also help you find what you are interested in. Such physical cue information may be key to identifying desired selections from library resources. Unfortunately, most digital experiences typically do not provide such cues without actually loading and viewing the work in digital form.

Thus, another reason why the electronic or digital world can make it even harder to find information than ever before has to do with the physical format of the information. The digital information may provide few or no outward cues or other physical characteristics that could help you to even find out what it is--let alone determine whether or not you are interested in it, unless such cues are provided through special purpose informational (for example, graphical) displays. On the Internet, everyone can be an electronic publisher, and everyone can organize their offerings differently--using visual cues of their own distinctive design (e.g., location on a web page, organization by their own system for guiding choices). As one example, one publisher might use a special purpose graphical representation such as the video kiosk to support an electronic video store. Other publishers may use different graphical representations altogether.

Historically, there has been no particular need for consistent selection standards in conventional, non-electronic store based businesses. Indeed, it is often the unique display and choice selection support for customers' decision processes that make the difference between a successful store and a failure. But in the electronic world--where your choice is not among a few stores but rather is a choice among potentially thousands or even millions of possibly useful web sites and truly vast numbers of digital containers--the lack of a consistent system for describing commercially significant variables that in the "real" world may normally be provided by the display context and/or customized information guidance resource (catalog book, location of goods by size, etc.) seriously undermines the ability of digital information consumers to identify their most desirable choices.

Adding to this absence of conventional cues, the enormity of available choices made available in cyberspace means that the digital information revolution, in order to be practical, must provide profoundly more powerful tools to filter potentially desirable opportunities from the over abundance of choices. In sum, the absence of the ability to efficiently filter from a dimensionally growing array of choices, can completely undermine the value of having such a great array of choices.

In the "real" world, commercial choices are based on going to the right "store" and using the overall arrays of available information to identify one's selection. However, as information in digital and electronic form becomes more and more important, the problem of relating to the vast stores of information will become a nightmare. For example, picture yourself in a store where each shopping aisle is miles long, and each item on the shelf is packaged in the same size and color container. In an actual store, the product manufacturers put their products into brightly colored and distinctively shaped packages to make sure the consumer can readily find and select their product. These visual cues distinguish, for example, between a house brand and a specific name brand, between low fat and regular foods, and between family size and small size containers.

On the Internet, a digital "store" is likely to be many stores with vast resources integrating products from many parties. If you were limited to conventional classification and matching mechanisms, you would be unable to sift through all the material to identify the commercially acceptable, i.e., an item representing the right information, at the right price, providing license rights that match your interests. Certainly, if each digital package looks the same, you are at a loss in making reasonable decisions. You can't tell one from another just by looking at it.

While information written on the "outside" of a digital package may be useful, you simply don't have the time to read all the packages, and anyway, each packager may use different words to describe the same thing and the descriptions may be difficult to understand. Some people may write a lot of information on the outside of their package, and others may write little or nothing on the outside of the package. If there is no universal system agreed upon by everyone for defining what information should be written on the outside of the package and how it should be formatted, using such a store would be painfully difficult even if you could limit the number of choices you were evaluating.

There is a Need For Efficient and Effective Selection Based, at Least in Part, on Rights Management Information

Unlike a real store where all breakfast cereals are shelved together and all soft drinks are in the same aisle, there may be no single, universal way to display the organization of all of the information in a "digital store" since, by its nature, digital information frequently has many implications and associated rules. For example, there now exist highly developed rights management systems such as described in U.S. Pat. No. 5,892,900, to Ginter et al., issued Apr. 6, 1999, for "Systems And Methods For Secure Transaction Management And Electronic Rights Protection (hereafter "Ginter et al")--the entire disclosure (including the drawings) of which is expressly incorporated into this application as if expressly set forth herein. Many rules associated with any given piece of digital information may, combinatorially, given rise to many, very different, commercial contexts that will influence the use decisions of different potential users in many different ways (e.g., cost, auditing, re-use, redistribution, regulatory requirements, etc.).

No readily available systems developed for the digital information arena provide similarly satisfying means that describe the many commercial rules and parameters found in individual custom catalogs, merchandise displays, product specifications, and license agreements. Further, no readily available mechanisms allow "surfing" across vast choice opportunities where electronic matching can single out those few preferred items.

As one example, picking an appropriate image may involve any or all of the following:

price,

republishing (redistribution) rights,

rights to extract portions,

certified usable in certain sovereignties (e.g., pornographic content not allowed in Saudi Arabia),

size,

format, etc.,

use and reuse administrative requirements (e.g., which clearinghouses are acceptable to rightsholders, what is the requirement for reporting usage information--is the name of your customer required, or only the use class(es) or none--is advertising embedded), and

other features.

No previously readily available technology allows one to efficiently make selections based on such criteria.

By their nature, and using the present inventions in combination with, amongst other things, "Ginter et al", the packages in a digital store may be "virtual" in nature--that is, they may be all mixed up to create many, differing products that can be displayed to a prospective customer organized in many different ways. This display may be a "narrowcasting" to a customer based upon his matching priorities, available digital information resources (e.g., repository, property, etc.) and associated, available classification information. In the absence of an effective classification and matching system designed to handle such information, digital information of a particular kind might be just about anywhere in the store, and very difficult to find since the organization of the stores digital information resources have not been "dynamically" shaped to the matching interests of the potential customer.

These Inventions Solve These Problems

The present inventions can help to solve these problems. It can give you or help you to find the things you like, need or want. For example, it can deliver to you, (including narrowcasting to you), or help you to find:

things that match your interests;

things that match your lifestyle;

things that match your habits;

things that match your personality;

things you can afford and/or accept your preferred payment method;

things that help you in your work;

things that help you in your play;

things that help you to help others;

things that other people who are similar to you have found helpful,

things that fulfill the commercial objective or requirements of your business activities; and

things that will make you happy and fulfilled.

The present inventions can expand your horizons by helping you to find interesting or important things, things that you enjoy, things that optimize your business efficiency, and things that help you make the best digital products or services you can--even if you didn't know precisely what or how to look for what you may need. It can also help you by allowing things you didn't know existed or know enough to look for--but that you may be interested in, want or need--to find you.

The Present Inventions Can Use "Metaclasses" to Take Multiple Classifications Into Account

In some areas, multiple classifications may already exist and thus it is important for a consumer to be able to find what he or she is looking for while taking into account not only that there may be multiple classifications, but also that some classifications may be more authoritative than others. For example, Consumer Reports may be more authoritative on certain topics than more casual reviews published, for example, in the local weekly newspapers.

As another example, consider a book that rates restaurants according several factors, including, for example, quality, price, type of food, atmosphere, and location. In some locations there may be many guides, but they may review different sets of restaurants. One guide may rate a particular restaurant highly while one or more others may consider it average or even poor. Guides or other sources of ratings, opinions, evaluations, recommendations, and/or value may not be equally authoritative, accurate, and/or useful in differing circumstances. One consumer may consider a guide written by a particular renowned expert to be more authoritative, accurate, and/or useful than a guide reflecting consumer polls or ballots. However, another consumer may prefer the latter because the second consumer may perceive the tastes of those contributing opinions to be closer to his or her own tastes than those of the experts.

In accordance with the present inventions, a person may be able to find a restaurant that meets specified criteria--for example, the highest quality, moderately priced Cantonese and/or Hunan Chinese food located in Boston or Atlanta--while weighting the results of the search in favor of reviews from travel books rather than from the local newspapers. As this example indicates, the searching may be according to class of authoritative source (and/or classes sources considered authoritative by the consumer) instead of weighting individual reviewers or sources. Thus in accordance with the present inventions, search may be performed at least in part based on classes of classes, or "metaclasses."

The Present Inventions Can Make Choices Easier

One simple way to look at some examples of the present inventions is as a highly sensitive electronic "matchmaker" that matches people or organizations with their best choices, or even selects choices automatically. The present inventions can match people and/or organizations with things and/or services, things with other things and/or services, and/or even people with other people. For example, the matching can be based on profiles that are a composite of preference profiles of one or more specific users, one or more user groups, and/or organizations--where the contribution of any given specific profile to the composite profile may be weighted according to the specific match circumstances such as the type and/or purpose of a given match activity.

FIG. 5 shows a simplified example of an electronic matchmaker that can match up two people with like interests. Sarah loves hiking, country and western music, gardening, movies and jogging. Mark loves movies, hiking, fast cars, country and western music, and baseball. The electronic matchmaker can look at the interests, personalities and/or other characteristics of these two people and determine that they are compatible and should be together--while maintaining, if desired, the confidentiality of personal information. That is, unlike conventional matchmaking services, the present inventions can keep personal information hidden from the service provider and all other parties and perform matching within a protected processing environment through the use of encryption and protected processing environment-based matching analysis.

For example, certain matching of facts that are maintained for authenticity may be first performed to narrow the search universe. Then, certain other matching of facts that are maintained for secrecy can be performed. For example, matching might be based on shared concerns such as where two parties who have a given disability (such as cancer or HIV infection) that is certified by an authority such as a physician who is certified to perform such certification; or the same income level and/or bank account (as certified by an employer and/or financial authority such as a bank). Some or all of such secret information may or may not be released to matched parties, as they may have authorized and/or as may have been required by law when a match is achieved (which itself may be automatically managed within a protected processing environment through the use of controls contributed by a governmental authority).

FIG. 5A shows an electronic matchmaker that matches an electronic publisher with mystery stories for his quarterly electronic mystery anthology, where the matching is based on price, redistribution rights, editing rights, attribution requirements (attributing authorship to the author), third party rating of the writers quality, length of story, and/or the topical focus of the story (for example). Here, rule managed business requirements of publisher and writers are matched allowing for great efficiency in matching, coordination of interests, and automation of electronic business processes and value chain activities.

The convenience of the "electronic matchmaker" provided in accordance with the present inventions extends to commerce in physical goods as well--as illustrated in FIG. 5b. In this non-limiting example, the electronic matchmaker is communicating to the consumer via the Internet and World Wide Web. The matchmaker has found the lowest quoted price for a Jeep sports utility model given, in this one example, a multitude of factors including:

model,

color,

options package,

availability, and

discounts resulting from the consumer's membership in certain classes (such as membership in the American Association of Retired Persons, membership in the American Automobile Association, and being a graduate of Stanford University).

Membership in these associations and alumni status may be conveyed or indicated by possession of a special electronic document called a "digital certificate," "membership card," and/or other digital credential that warrants or attests to some fact or facts.

Thus, the electronic matchmaker provided in accordance with these inventions can also match people with things. FIG. 6 shows two people, Harry and Tim. Harry loves sports most of all, but also wants to know a little about what is going on in the business world. The business world is most important to Tim, but he likes to keep up with the baseball scores. The electronic matchmaker in accordance with these inventions can learn about what Harry and Tim each like, and can provide information to a publisher so the publisher can narrowcast a newspaper or other publication customized for each of them. A newspaper company can narrowcast to Harry lots of sports information in his newspaper, and it can narrowcast to Tim mostly business information in his newspaper. In another example, Harry's newspaper may be uniquely created for him, differing from all other customized newspapers that emphasize sports over business information. But information that Harry and Tim respectively want to maintain as authentic or secret can be managed as such.

The electronic matchmaker can also match things with other things. FIG. 7 shows how the electronic matchmaker can help a student put together a school project about big cats. The electronic matchmaker can help the student locate and select articles and other material about various kinds of big cats. The electronic matchmaker can, for example, determine that different articles about tigers, lions and cheetahs are all about big cats--but that articles about elephants and giraffes are not about big cats. If there is a charge for certain items, the electronic matchmaker can find only those items that the student can afford, and can make sure the student has the right to print pictures of the big cats. The electronic matchmaker can help the student to collect this information together so the student can make a colorful poster about big cats.

The electronic matchmaker can match up all sorts of different kinds of things. FIG. 8 shows the electronic matchmaker looking at three different objects. The matchmaker can determine that even though objects A and C are not identical, they are sufficiently similar that they should be grouped together for a certain purpose. The electronic matchmaker can determine that for this purpose, object B is too different and should not be grouped with objects A and C. For a different purpose, the electronic matchmaker may determine that objects A, B and C ought to be grouped together.

The Present Inventions Can Make Use of Rights Management Information

How does the electronic matchmaker find out the information it needs to match or classify people and things? In accordance with a feature provided by these inventions, the electronic matchmaker gets information about people and things by using automated, computerized processes. Those processes can use a special kind of information sometimes known as rights management information. Rights management information may include electronic rules and/or their consequences. The electronic matchmaker can also use information other than rights management information.

An example of rights management information includes certain records about what a computer does and how it does it. In one simple example, records may give permission to read a particular news article if that the customer is willing to pay a nickel to purchase the article and that the nickel may be paid using a budget provided by a credit card company or with electronic cash. A customer might, for example, seek only news articles from providers that take electronic cash and/or process information with a certain information clearinghouse as described in U.S. patent application Ser. No. 08/699,712 to Shear et al., filed Aug. 12, 1996, for "Trusted Infrastructure Support Systems, Methods And Techniques For Secure Electronic Commerce Electronic Transactions And Rights Management" (hereafter "Shear et al")--the entire disclosure (including the drawings) of which is expressly incorporated into this application as if expressly set forth herein.

The Present Inventions Can Maintain Privacy

FIG. 9 shows one way in which the electronic matchmaker can get information about a person. In this example, the electronic matchmaker asks Jill to fill out a computer questionnaire about what she likes. The questionnaire can also ask Jill what information she wishes to be maintained as authentic, and what information (e.g., encrypted by the system) may be used for secure matching only within a protected processing environment and can not be released to another party, or only to certain specified parties. The questionnaire answering process may be directly managed by a protected processing environment to ensure integrity and secrecy, as appropriate.

For example, the questionnaire may ask Jill whether she likes baseball and whether she is interested in volcanoes. The electronic matchmaker can also ask Jill if it is okay to look at records her computer maintains about what she has used her computer for in the past. These computer records (which the computer can maintain securely so that no one can get to them without Jill's permission) can keep a history of everything Jill has looked at using her computer over the past month and/or other time period--this process being managed, for example, through the use of a system such as described in the "Ginter et al."

Looking at FIG. 10, Jill may have used her computer last week to look at information about baseball, volcanoes and Jeeps. With Jill's permission, the electronic matchmaker can employ a protected processing environment 154 (schematically shown here as a tamper-resistant "chip" within the computer--but it can be hardware-based, software-based, or a combination of hardware and software) to look at the computer's history records and use them to help match Jill up with other kinds of things she is or may be interested in. For example, the electronic matchmaker can let an electronic publisher or other provider or information gatherer (e.g., market survey conductor, etc.) know that Jill is interested in team sports, geology and sports utility vehicles with or without more revealing detail--as managed by Jill's choices and/or rights management rules and controls executing in her computer's protected processing environment 154. The provider can send information to Jill--either automatically or at Jill's request--about other, related things that Jill may be interested in.

FIG. 11 shows an example of how rights management and other information Jill's computer maintains about her past usage can be useful in matching Jill up with things she may need or want. The computer history records can, for example, show that Jill looked at hockey information for three hours and football information for five hours during the past week. They can indicate that Jill uses a Discover credit card to pay for things, usually spends less that $10 per item, averages $40 per month in such expenses, and almost never buys new programs for her computer.

The electronic matchmaker can, with and subject to Jill's permission, look at and analyze this information. As one example, the electronic matchmaker can analyze relevant rules and controls provided by third parties who have rights in such information--where such rules are controlled, for example, by Jill's computer's protected processing environment 154. It can also look at and analyze Jill's response to computer questionnaires indicating that she likes baseball and football. The electronic matchmaker can, based on all of this information, automatically select and obtain videos and/or other publications for Jill about team sports and that cost less than $10 and that accept payment using a Discover card, so that Jill can preview and select those in which she may have a particular interest and desire to acquire.

FIG. 12 shows that the electronic matchmaker can take into account computer history records for lots of different people. The electronic matchmaker can work with other rights management related computer systems such as "usage clearinghouses" (non-limiting examples of which are described in each of "Ginter et al" and "Shear et al") to efficiently collect rights management related information. The ability to collect history records from many different people can be very useful. For example, this can allow the electronic matchmaker to distinguish between things that are very popular and things that are not so popular.

The present inventions provide great increases in efficiency and convenience. It can save you a lot of time and effort. It can allow computers to do a lot of the work so you don't have to. It can allow you to compete with larger businesses--and allow large business to function more efficiently--by allowing the location of resources particularly appropriate for certain business activities. You can delegate certain complex tasks to a computer, freeing you to be more productive and satisfied with electronic activities. These automated processes can be "smart" without being intrusive. For example, they can learn about your behavior, preferences, changing interests, and even your personality, and can then predict your future interests based on your past behavior and interest expressions. These processes can ensure confidentiality and privacy--so that no one can find out detailed information about you without your consent. Across the full range of personal and business activities, the present inventions allow a degree of basic efficiency, including automation and optimization of previously very time consuming activities, so that interests and possible resources are truly best matched.

The present inventions handle many kinds of important issues and addresses the widest range of information and rights and automation possibilities. For example, the present inventions are capable of handling (but are not limited to):

consumer information;

computer information;

business information;

entertainment information;

other content information;

information about physical products;

all other kinds of information.

It can reflect and employ all kinds of rights to optimize matching processes, including:

content rights;

privacy rights;

governmental and societal rights;

provider rights;

distributor rights;

consumer rights;

workflow rights;

other value chain participant rights;

work flow rights;

business and personal rights and processes of all kinds.

It can employ all kinds of parameter information, including:

budget,

pricing

redistribution

location (of party, item, etc.)

privacy

identity authenticity and/or specificity

any other parameter information.

Pricing (for example the price of a specific item) can be used in matching based upon price per unit and/ or total price for a volume purchase, price for renting, right to redistribute, cost for redistributing items, etc.

Privacy can be used for establishing matching contingent upon usage reporting requirements for viewing, printing, extracting, dedistributing, listening, payment, and/or requiring the reporting of other information such as personal demographics such as credit worthiness, stored value information, age, sex, marital status, race, religion, and/or usage based generated profiling information based materially upon, for example, a users history of usage of electronic content and/or commercial transactions, etc.

Identity can be used for matching based upon, for example, such as the presence of one or more specific, class, and/or classes of certificates, including, for example, specific participant and/or group of participant, including value chain certificates as described in "Shear et al".

With the inventions described herein, commercial requirement attributes embodied in rules (controls and control parameter data) are employed in classification structures that are referenced by search mechanisms, either, for example, directly through reading rule information maintained in readable (not encrypted) but authentic (protected for integrity) form, through reading rule information maintained securely, through processes employing a protected processing environment 154 of a VDE node, and/or through the creation of one or more indexes and/or like purpose structures, that, directly, and/or through processes employing a protected processing environment 154, automatically compile commercial and other relevant (e.g., societal regulatory information such as a given jurisdiction's copyright, content access and/or taxation regulations) for classification/matching purposes.

The present inventions can employ computer and communication capabilities to identify information, including:

topical classification such as described by conventional library classification systems,

commercial characterizations--including commercial parameter data such as pricing, size, quality, specific redistribution rights, etc.,

creator (e.g., a publisher or manufacturer), distributor, societal, user, and other participant interests information,

information generated by automated profiling of any and all of such parties or collections of parties,

matching (including electronically negotiating a match) between the interests of any of such parties,

where appropriate, the use of statistical procedures, expert systems, and artificial intelligence tools for profiling creation and/or analysis, matching, and/or negotiation.

The present inventions thus provide for optimal user, provider, and societal use of electronic cyberspace resources (for example, digital information objects available across the Internet, sent by direct broadcast satellite, transmitted over a cable TV system, and/or distributed on optical disk).

Of particular importance is the notion of classes of content, classes of users, and classes of providers. For example, the present inventions can make use of any/all of the following:

topical identification, for example, such as information represented in typical library subject and/or author and/or catalog and/or keyword search and retrieval information systems;

any commercial requirements, associated with the use of electronic information (and/or to products, including non-electronic products, and/or to any service), including information embodied in encrypted rules (controls and/or parameter data) governing rights in electronic value chain and electronic interaction contexts, and further including information guaranteed for integrity;

any information descriptive of an available resource (which may include any information, product, and/or service, whether available in electronic and/or physical forms) such as: the quality of a digital product as evaluated and ranked and/or otherwise specified by one or more third parties and/or independent third parties (e.g., Consumer Reports, a trusted friend, and/or a professional advisor), the size of a product, length in time in business of a service or in the market of a product, a product's or service's market share, and/or subject governmentally and/or other societally imposed rules and/or integrity guaranteed descriptions, including any associated regulatory requirements, such as societal requirements granting and/or reporting access to information, for example, information on how to create a nuclear bomb to a confidential government auditing agency (this allowing free access to information while protecting societal rights);

any information descriptive of a user and/or department and/or organization and/or class of users and/or departments and/or organizations (including, for example, such descriptive information encrypted and/or guaranteed for integrity) wherein such information may include, for example, name, physical and/or network and/or cyber-wide logical network location, organizational and/or departmental memberships, demographic information, credit and/or trustworthiness information, and profile preference and usage history information, including any generated profile information reflecting underlying preferences, and/or classes based on said descriptive information and/or profiles.

Some Of The Advantageous Features And Characteristics Provided By The Present Inventions

The classification, matching, narrowcasting, analysis, profiling, negotiation, and selection capabilities of the present inventions include the following capabilities (listed items are not mutually exclusive of each other but exemplary samples):

Enables highly efficient provision of classes of information, entertainment, and/or services to classes of individuals and/or entities that have (and/or may obtain) the right(s) to such information and are likely to find identified information interesting, useful, and/or entertaining.

The present inventions also provide systems and methods for efficiently determining class hierarchies, classification schemes, categories, and/or category schemes and/or the assignment of objects, persons and/or things to said class hierarchies, classification schemes, categories, and/or category schemes using at least some rights management information.

Helps systems, groups, and/or individuals classify, locate, and/or obtain specific information and/or classes of information made available through so-called "publish and subscribe" systems and methods using, among other things, subject-based addressing and/or messaging-based protocol layers.

Provides fundamentally important commercial and societal rules based filtering to identify desired electronic information and/or electronic information containers through the use of classification structures, profiling technology, and matching mechanisms that harness the vast information opportunities in cyberspace by matching the information needs of users against commercial and/or societal rules related to the use of available information resources, including, for example, commercial and/or societal consequences of digital information use imposed as provider requirements and specified through the use of, and enforced by the use of, a trusted rights management system such as described in "Ginter et al".

Enables content creators and/or distributors to efficiently "stock the shelves" of retail electronic content outlets and similar merchanisers (both electronic and hard goods) with products and/or services most likely to be purchased and/or used by the customers of such merchanisers. This includes both identifying and "stocking" the most desirable products and/or other user desired resources and optimally presenting such products and/or other resources in a manner optimized for specific users and/or user classes.

Matching may be based on history of matching, that is, matching derived at least in part from previous matching, one non-exhaustive example of which includes learned matching for increasing efficiency.

Enables matching for value chains where the matching is against a plurality of co-participating value chain parties requirements and/or profiles against match opportunities, and/or matching by matches comprised of match input and/or aggregation of match rule sets of providers used to "dock" with one or more user needs, interests, requirements match sets.

Helps match persons and/or things using fuzzy matching, artificial intelligence (e.g., expert systems), and other methods that that match using plural match sets from providers and/or receivers.

Makes search easier by using smart agents that match at least in part using at least one class.

Helps bring buyers and sellers together through cross matching, where both parties offer to provide and/or receive content and/or physical goods for consideration, including barter matching and negotiated barter and other kinds of matching.

Helps potential customers find those members (e.g., objects such as digital information containers) of any one or more classes of content most useful, entertaining, and/or interesting to them.

Facilitates organizations securely and efficiently acquiring and distributing for internal use certain classes of content available from external providers and/or more securely and/or efficiently managing classes of their own content, including being able to authorize certain classes of employees to use specified classes of internal and/or external content.

Efficiently supporting matching between users and digital information where participants in a chain of handling and control have specified rules and usage consequences for such digital information that may depend on class membership, for example, on class(es) of content and/or class(es) of value chain participants and/or classes of electronic events, wherein such participants include, for example, users and/or participants contributing rules and consequences.

Enables first individuals and/or organzations to locate efficiently other individuals, organizations, products, and/or services who have certain characteristics that corresponds to such first individuals' and/or organizations' interests, including interests generated by profiling information locally gathered through local event auditing at a VDE installation.

Facilitates businesses informing a customer about things of special interest to her or him, such as classes of goods, services, and/or content, including directing such information to a customer at least in part based on profiling information locally gathered at a VDE installation through local event auditing at a VDE installation.

Allows trading companies to match suppliers of certain classes of goods and/or services with those who desire to purchase and/or use those classes of goods and/or services, wherein such matches may include fulling a commercial business interaction and may further include one or more sequences of matches and/or nested matches (a sequence and/or grouping of matches within a given organization or group, wherein such matches may be required to occur in a certain order and/or participate along with other matches in a group of matches before a given match is fulfilled).

Enhances equity portfolio management by making easier for traders to identify those equities having certain desired characteristics, such as belonging to the class of equities that will have the greatest positive effect on the value of the trader's portfolio given certain classes of information and assumptions. Such matches may take into account information external to the fulfilment of a given trade, for example, one or more certain other market or specific variable thresholds must be met before an equity is traded, such as a certain rise in the an index stock value of, and/or revenue of, certain one or more network hardware suppliers before a certain quantity of equity is purchased at a certain price for stock of a certain network hardware supplier raw network component manufacturer, and wherein, for example, such determinations can be performed highly efficiently at a user VDE installation as the point of control, where such node receives such trusted information in, for example, VDE containers, as is necessary for a control decision to occur to purchase such equity of such network hardware supplier raw component manufacturer.

Makes easier automated foreign currency exchange by enabling currency traders to identify members of the class of possible trades and/or conversions that are likely to produce the best returns and/or minimize losses.

Helps consumers and organizations manage their affairs more efficiently and effectively and helps providers of services by automatically matching users with services that meet certain specified criteria, such as, for example, U.S. and Swiss banks offering the highest interest rates on certain time based classes of bank deposit instruments.

Enables distributers of software and other content to identify one or more classes of users who are most likely to be interested in purchasing or otherwise using certain classes of software.

Enables rightsholders to employ rules and/or usage consequences dependent on membership in one or more classes where class membership may be indicated by posession of a special digital document called a "certificate."

Enables rightsholders to employ rules and/or usage consequences at least partially dependent on roles and responsibilities within an organization, where those roles and responsibilities may be indicated by posession of a digital certificate, digital membeship card, and/or other digital credential.

Facilitates more efficient automation of manufacturing and other workflow processes by, for example, matching certain manufacturing steps and/or processes with performance parameter data associated with available classes of equipment capable of performing those steps and/or processes.

Makes easier the administration and enforcement of government and/or societal rights by, for example, providing matching means for automatically applying certain classes of tax rules to appropriate classes of sales and other transactions.

Enables altering the presentation of information and/or other content depending on the matching between preferences of the user and one or more classes of content being presented.

Enables processing or altering (narrowcasting) of an event (e.g., the presentation of information and/or other content), for example, dynamically adjusting the content of an event, in response to a matching among the preferences and/or reactions of a user and/or user group, one or more classes of content being processed through one or more events, one or more classes of one or more users participating in and/or otherwise employing the one or more events, and/or event controls (i.e., rules and/or parameter data).

Allows the rules and usage consequences and the presentation of information to vary according to the difficulty of the information, including, for example, adjusting the difficulty of an electronic game so that it is neither too frustratingly difficult nor too easy to use.

Enables a user to efficiently locate content in one or more particular classes, where class is defined at least in part by weighted topical classification, where, for example, a document or other object is classified in one or more categories where at least one category reflects the absolute or relative attention given to that class in the object being classified.

Facilitates users' creation of a new document from parts of two or more documents, where at least one of such parts is identified and/or retrieved based upon matching the part's membership in one or more classes identified by trusted, commercial controls employed through the use of a rights management system.

Enables users to search for, locate, and use only those parts of a document that belong to one or more specified classes, including those parts having certain commercial controls, for example, reflecting acceptable usage restrictions and/or pricing.

Enhances search and retrieval by creating new classes of content discriptors that incorporate various dispirate standards for content description and/or location.

Allows consumers to easily locate services having certain specified characteristics, for example, gambling services offering the most favorable odds and/or specified rules for a particular game or games.

Helps consumers obtain certain classes of tickets to certain classes of events.

The above capabilities, and others described in this application, are often ideally managed by distributed commerce nodes of a distributed, rights management environment embedded in or otherwise connected to the operating system clients of a distributed computing environment such as described in "Ginter et al" and further described in "Shear et al", and employing, for example, rules, integrity management, container, negotiation, clearinghouse services, and trusted processing capabilities described in "Ginter et al" and "Shear et al".

The Present Inventions Make Use Of Many Kinds Of Information And/Or Data

As discussed above, these inventions provide, among other things, matching, classification, narrowcasting, and/or selection based on rights management and other information. In particular preferred examples, these matching, classification, narrowcasting, and/or selection processes and/or techniques may be based at least in part on rights management information. The rights management information may be an input to the process, it may be an output from the process, and/or the process can be controlled at least in part by rights management information. Information in addition to, or other than, rights management information may also be an input, an output, and/or a basis for controlling, the process and/or techniques.

Rights management information may be directly or indirectly inputted to the matching, classification and/or selection process. For example, rights management controls, rules and/or their consequences may be an input. Examples of such controls and/or rules include object registration related control set data, user related control set data and/or computer related control set data. In addition or alternatively, information provided based on control sets or rules and their consequences may be inputted. The following are examples of such information that may be provided based, for example, on rules and consequences:

information exhaust;

user questionnaires,

audit trail related information;

aggregated usage data;

information measuring or otherwise related to user behavior;

information measuring or otherwise related to user preferences;

information measuring or otherwise related to user personality;

information measuring or otherwise related to group behavior;

information measuring or otherwise related to group preferences;

information measuring or otherwise related to group culture

information measuring or otherwise related to organizational behavior;

information measuring or otherwise related to organizational preferences;

information measuring or otherwise related to organizational culture;

information measuring or otherwise related to institutional behavior;

information measuring or otherwise related to institutional preferences;

information measuring or otherwise related to institutional culture;

information measuring or otherwise related to governmental behavior;

information measuring or otherwise related to governmental preferences;

information measuring or otherwise related to governmental culture;

information measuring or otherwise related to societal behavior;

information measuring or otherwise related to societal preferences;

information measuring or otherwise related to societal culture;

object history related information;

other types of information;

any combinations of information including, some, all or none of the information set forth above.

The processes, techniques and/or systems provided in accordance with these inventions may output rights management related information such as, for example:

one or more control sets;

various rules and/or consequences;

information used by control sets;

certificates;

other rights management information.

In accordance with various preferred embodiments provided by these inventions, information other than rights management information may also be used, at least in part, as an input, output and/or to control the matching, classification, narrowcasting, and/or selection processes, systems and/or techniques. Examples of such information include:

content object information;

full text

portions of objects

portions of sub-objects

abstracts

metadata

other content object related information

user information

census information

purchasing habits

credit and financial transaction related information

governmental records

responses to questionnaires

survey results

other user information

computer related information

identification information

configuration information

other computer related information

combinations of information.

Matching/Classifying/Selection

Systems, methods and techniques provided in accordance with these inventions can classify a variety of types of things including, for example:

people

computers

content

events

transactions

objects of all types

combinations of things;

combinations of people and things.

The matching, classifying and/or selecting processes provided in accordance with these inventions are very flexible and useful. For example, they may be used to associate people with information, information with other information, people with other people, appliances with people, appliances with information, and appliances with other appliances. The present inventions in their preferred examples can associate any kind of information, object or thing with any other kind of information, object or thing.

Different Associations Between Classes and Rights

The processes, systems and/or techniques provided in accordance with these inventions can provide and/or take into account many different kinds of associations between classes and rights. For example, they can look at what rights are available to a user, computer, data structure or any other object. They can also look to rights selected by an object (for example, the subset of rights a user has chosen or otherwise identified). Alternatively or in addition, they can look to rights that have been exercised by a user or in conjunction with an object or other thing, and they can look to the consequences of exercising such a right(s).

Embodiments in Accordance With the Present Inventions Can Be Used to Define Classes Based on Uni-Dimensional and/or Multi-Dimensional Attributes and/or Characteristics

Example processes, systems and/or techniques provided in accordance with these inventions can be used to define classes based on uni-dimensional and/or multi-dimensional attributes and/or characteristics. Any one or more attributes can be used. The attributes and/or characteristics can be flexibly defined. They may define groups or classes containing elements sharing certain attributes in common. There can, for example, be a spectrum of classification that takes into account gray areas as to whether a particular person or thing possesses a certain one or a number of particular attributes and/or characteristics. Or classification may have a higher degree of certainty or definition. For example, a process can test to determine whether particular people or things are inside or outside of particular classes or groups based on one or a number of attributes or characteristics (for example, whether you live in Denver, are under the age of 25 and are single). In accordance with additional specific features provided by these inventions, there may be a minimum number of different classes set up to "cover" a particular situation--with every person or thing either being within or outside of a given, disjoint class or group.

Preferred Examples In Accordance With The Present Inventions Are Extensible to Accommodate Changing Conditions

The systems, methods and/or techniques provided by these inventions are extensible to accommodate changing conditions. For example, they can be made to readily adapt to changes in rules, consequences, topics, areas and/or subjects pertaining to groups such as, for example categories, and any other variable. Furthermore, partially and/or entirely new variables may be introduced to one or more existing sets of variables--for example, to extend or otherwise modify a model to account for additional variables, to apply a new strategy, to adapt to new network and/or installation circumstances, to adapt to new user factors, to change analysis and/or other processing characteristics, and so on.

Preferred Examples In Accordance With The Present Inventions Are Compatible With Pre-Existing or Any New Classification Techniques or Arrangements

The example systems, methods and/or techniques provided by these inventions can be made fully compatible with any classification and/or categorization means, method, process, system, technique, algorithm, program, and/or procedure, presently known or unknown, for determining class and/or category structures, definitions, and/or hierarchies, and/or the assignment of at least one object, person, thing, and/or member to at least one class and/or category, that without limitation may be:

implemented by computer and/or other means; and/or

based upon discrete and/or continous mathematics; and/or

using nominal, ordinal, interval, ratio and/or any other measurement scale and/or measurement mode; and/or

including parameter data; and/or

entail linear and/or non-linear estimation methods; and/or

any other methods.

For example, classification can be performed using any or all of the following example classification techniques:

Statistical techniques that identify one or more clusters of cases sharing similar profiles and/or features, including any of the family of cluster analysis methods, for example, those described in Hartigan (Hartigan, J. A., Clustering Algorithms, New York: Wiley, 1975);

Methods for numerical taxonomy, for example, as described, for example, by Sneath and Sokal (Sneath, Peter H. A. and Robert R. Sokal, Numerical Taxonomy: The Principals and Practice of Numerical Classification, San Francisco: W. H. Freeman, 1973);

Any of the methods for cluster analysis, factor analysis, components analysis, and other similar data reduction/classifiction methods, for example, those implemented in popular statistical and data analysis systems known to those skilled in the arts, for example, SAS and/or SPSS;

Pattern classification techniques, including components analysis and neural approaches, for example, those described by, for example, Schurmann (Schurmann, Jurgen, Pattern Classification: A Unified View of Statistical and Neural Approaches, New York: John Wiley & Sons, 1966);

Statistical techniques that identify one or more underlying dimensions of qualities, traits, features, characteristics, etc., and assign parameter data indicating the extent to which a given case has, possesses, and/or may be characterized by the underlying dimension, factor, class, etc. and/or result in the definition of at least one class and/or the assignment of at least one case to at least one class, for example, as described by Harman (Harman, Harry H., Modern Factor Analysis, 3rd ed. rev., Chicago: University of Chicago Press), and/or as implemented by SAS and/or SPSS and/or other statistical analysis programs.

Statistical methods that employ fuzzy logic and/or fuzzy measurement and/or whose assignment to at least one class entails probabilities different from 1 or zero.

Baysian statistical classification techniques that use estimates of prior probabilities in determining class definitions and/or the assignment of at least one case to at least one class;

Any statistical and/or graphical classification and/or data reduction method that uses rotation of reference axes, regardless of whether orthogonal or oblique rotations are used, for example, as described in Harman, and as implemented in SAS and/or SPSS and/or other statistical programs;

Statistical methods for two and three way multidimensional scaling, for example, the methods described by Kruskal and Wish (Krusgal Joseph B. and Myron Wish, Multidimensional Scaling, Beverly Hills, Calif.: Sage Publications, 1978), and/or by Shepard, et al. (Shepard, Roger N., A. Kimball Romney, and Sara Beth Nerlove, Multidimensional Scaling: Theory and Applications in the Behavioral Sciences, New York: Seminar Press, 1972);

Knowedge based approaches to classification, for example, as described by, for example, Stefik (Stefik, Mark, "Introduction to Knowledge Systems," San Francisco: Morgan Kauffman, 1995); and

any other classification techniques or arrangements pre-existing or yet to be developed.

Preferred Examples In Accordance With The Present Inventions Are Fully Compatible With A Wide Array of Technologies Including the Distributed Commerce Utility System and the Virtual Distribution Environment

Systems, methods and/or techniques provided in accordance with these inventions build upon and can work with the arrangements disclosed in "Ginter et al"; "Shear et al"; and other technology related to transaction and/or rights management, security, privacy and/or electronic commerce.

For example, the present inventions can make particular use of the security, efficiency, privacy, and other features and advantages provided by the Virtual Distribution Environment described in "Ginter et al".

As another example, a matching and classification arrangement can be constructed as a distributed commerce utility system as described in "Shear et al". The present inventions can work with other distributed commerce utility systems, and can enhance or be a part of other commerce utility systems.

By way of non-exhaustive, more specific examples, the present inventions can be used in combination with (and/or make use of) any or all of the following broad array of electronic commerce technologies that enable secure, distributed, peer-to-peer electronic rights, event, and/or transaction management capabilities:

a "VDE" ("virtual distribution environment") providing, for example, a family of technologies by which applications can be created, modified, and/or reused;

a standardized control and container environment which facilitates interoperability of electronic appliances and efficient creation of electronic commerce applications and models;

a programmable, secure electronic transaction management foundation having reusable and extensible executable components;

seamless integration into host operating environments of electronic appliances or direct employment of such technologies in electronic commerce applications;

cyberspace digital content rights and transaction management control systems that may operate in whole or in part over Internets, Intranets, optical media and/or over other digital communications media;

support of an electronic "world" within which most forms of electronic transaction such as content usage, distribution, auditing, reporting, and payment activities can be managed;

Transaction Operating Systems (operating systems that have integrated secure, distributed, and programmable transaction and/or event management capabilities);

Rights Operating Systems (operating systems that have integrated, distributed, and programmable rights management capabilities);

secure content container management;

clearinghouse functions related to content usage;

overall electronic commerce architectures that provide electronic commerce automation through the use of secure, distributed digital events management;

the general enablement of traditional commerce behavior in the digital commerce world;

enhanced inherent, distributed efficiencies of conventional commerce practices with powerful, reliable electronic security, and with the programmability and electronic automation efficiencies made possible by modern computing;

trusted operation of a freely configurable, highly efficient, general purpose digital marketplace in which parties "come together" to establish commercial relationships;

support of "real" commerce in an electronic form (that is, the progressive creation of commercial relationships that form, over time, a network of interrelated agreements representing a value chain business model);

enabling content control information to develop through the interaction of (and/or negotiation between) securely created and independently submitted sets of content and/or appliance control information;

interconnection of appliances providing a foundation for much greater electronic interaction and the evolution of electronic commerce;

a variety of capabilities for implementing an electronic commerce environment;

a neutral, general purpose platform for commerce;

an architecture that avoids reflecting specific distribution biases, administrative and control perspectives, and content types;

a broad-spectrum, fundamentally configurable and portable, electronic transaction control, distributing, usage, auditing, reporting, and payment operating environment;

systems and methods that uniquely enable electronic commerce participants to protect their interests during the sequence of activities comprising an electronic commerce model;

ability of commerce participants to assure protection by specifying rules and controls that monitor and enforce their interests during the processing of remote commerce events;

permitting commerce participants to efficiently participate in, and manage, the distributed electronic activities of a digital value chain;

allowing commerce model participants to, for example, securely and cooperatively govern and automate the distributed electronic activities comprising their collective electronic business models;

allowing commerce model participants to securely contribute electronic rules and controls that represent their "electronic" interests;

rules and controls that extend a "Virtual Presence.TM." through which the commerce participants govern remote value chain activities according to their respective, mutually agreed to rights;

a Virtual Presence taking